Files
Magnus Hedemark fe5b275d00 feat: add haystack — expert skill for production search pipelines
Greenfield SkillOpt: 3 epochs for deepset Haystack skill.
Pipeline DAG model, document stores, retrievers, evaluation, deployment.

Epoch 1 — Prominence: Hard-gate on Pipeline DAG vs LCEL pipe model
Epoch 2 — Decision Guidance: Where to Start, Framework Routing Guide
Epoch 3 — Pattern Expansion: Hybrid RAG pattern, evaluation pipeline, deployment

11 files: SKILL.md, 6 references, 3 templates, 1 script.
2026-07-09 14:53:43 -04:00

1.7 KiB

Haystack Document Stores

Document stores are the persistence layer. All share the same write/query interface.

Available Stores

Store Production Setup
InMemoryDocumentStore Dev only Built-in, no setup
ElasticsearchDocumentStore Yes pip install elasticsearch-haystack, running ES cluster
PineconeDocumentStore Yes pip install pinecone-haystack, API key
WeaviateDocumentStore Yes pip install weaviate-haystack, running Weaviate
PGVectorStore Yes pip install pgvector-haystack, PostgreSQL instance
ChromaDocumentStore Dev pip install chroma-haystack

Common Operations

# Write documents
from haystack.document_stores.in_memory import InMemoryDocumentStore
from haystack import Document

doc_store = InMemoryDocumentStore()
doc_store.write_documents([
    Document(content="Haystack is a framework for building search systems."),
    Document(content="It uses pipeline-based architecture.")
])

# Query (BM25 by default)
results = doc_store.query("What is Haystack?", top_k=3)

Metadata Filtering

from haystack.document_stores.filters import document_store_filter

filtered = doc_store.filter_documents({
    "field": "meta.source",
    "operator": "==",
    "value": "internal"
})

Store Selection Guide

  • InMemoryDocumentStore — prototyping, testing, small datasets
  • ElasticsearchDocumentStore — production search at scale, full-text + vector
  • PineconeDocumentStore — serverless vector search, large-scale embedding retrieval
  • WeaviateDocumentStore — hybrid search with built-in vectorization
  • PGVectorStore — if you already use PostgreSQL, minimal infrastructure overhead